Huawei technologies co., ltd. (20240273364). DATA PROCESSING METHOD, APPARATUS, AND SYSTEM simplified abstract
Contents
- 1 DATA PROCESSING METHOD, APPARATUS, AND SYSTEM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DATA PROCESSING METHOD, APPARATUS, AND SYSTEM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about the Technology
- 1.13 Original Abstract Submitted
DATA PROCESSING METHOD, APPARATUS, AND SYSTEM
Organization Name
Inventor(s)
Quanchong Huang of Hangzhou (CN)
DATA PROCESSING METHOD, APPARATUS, AND SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240273364 titled 'DATA PROCESSING METHOD, APPARATUS, AND SYSTEM
Simplified Explanation
The patent application describes a method where a cloud-side device trains a neural network deployed on an edge device using data collected by the edge device.
Key Features and Innovation
- Iterative training on a neural network deployed on an edge device.
- Cloud-side device obtains training set based on application scenario feature.
- Training set includes data from edge device and sample data related to the application scenario feature.
- Trained neural network is deployed back on the edge device.
Potential Applications
This technology can be used in various fields such as IoT, smart devices, and edge computing applications.
Problems Solved
This technology addresses the need for efficient training of neural networks on edge devices without relying heavily on cloud resources.
Benefits
- Reduced latency in data processing.
- Improved privacy and security by keeping data processing on the edge device.
- Enhanced efficiency in training neural networks for specific application scenarios.
Commercial Applications
- Edge computing solutions for IoT devices.
- Smart home automation systems.
- Industrial automation processes.
Prior Art
Readers can explore prior research in the fields of edge computing, neural network training on edge devices, and cloud-edge collaboration in data processing.
Frequently Updated Research
Stay updated on the latest advancements in edge computing, neural network training techniques, and cloud-edge integration for data processing.
Questions about the Technology
How does this technology improve data processing efficiency on edge devices?
This technology enhances data processing efficiency on edge devices by allowing iterative training of neural networks without relying heavily on cloud resources.
What are the potential applications of this technology beyond IoT devices?
This technology can also be applied in smart devices, industrial automation, and various edge computing applications.
Original Abstract Submitted
in a data processing method, when performing iterative training on a first neural network deployed on a first edge device, a cloud-side device obtains a first training set based on an application scenario feature of data collected by the first edge device. the first training set includes the data of the first edge device and sample data associated with the application scenario feature. the cloud-side device obtains a trained first neural network based on the first training set and the first neural network deployed on the first edge device. the cloud-side device then deploys the trained first neural network on the first edge device.
